A novel framework for closed-loop robotic motion simulation - part II: Motion cueing design and experimental validation

Giordano, Paolo Robuffo; Masone, Carlo; Tesch, Joachim; Breidt, Martin; Pollini, Lorenzo; Bülthoff, Heinrich H.

doi:10.1109/robot.2010.5509945

Cited by 19 publications

(18 citation statements)

References 16 publications

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“…For this study, the motion was generated using a classical washout filter, adapted to the cylindrical workspace of the CMS. 19 No scaling or saturation was applied to the translational and rotational channels, with the only exception of forward linear acceleration, which was scaled by 0.4. Lateral acceleration of the simulated vehicle was high-pass filtered before being transformed into sway motion of the simulator cabin with the following filter:…”

Section: Setupmentioning

confidence: 99%

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Roll rate perceptual thresholds in active and passive curve driving simulation

et al. 2016

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In driving simulation, simulator tilt is used to reproduce sustained linear acceleration. In order to feel realistic, this tilt is performed at a rate below the human tilt rate detection threshold, which is usually assumed constant. However, it is known that many factors affect the threshold, such as visual information, simulator motion in additional directions, or the driver’s active effort required for controlling the vehicle. Here we investigated the effect of these factors on the roll rate detection threshold during simulated curve driving. Ten participants reported whether they detected roll motion in multiple trials during simulated curve driving, while roll rate was varied over trials. Roll rate detection thresholds were measured under four conditions. In the first three conditions, participants were moved passively through a curve with the following: (i) roll only in darkness; (ii) combined roll/sway in darkness; (iii) combined roll/sway and visual information. In the fourth (iv) condition participants actively drove through the curve. The results showed that roll rate thresholds in simulated curve driving increase, that is, sensitivity decreases, when the roll tilt is combined with sway motion. Moreover, an active control task seemed to further increase the detection threshold, that is, impair motion sensitivity, but with large individual differences. We hypothesize that this is related to the level of immersion during the task.

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Section: Setupmentioning

confidence: 99%

“…As typically done in standard washout schemes, this lowfrequency acceleration signal was reproduced by rolling the simulator cabin (tilt coordination, see Robuffo Giordano et al 19 ) while the maximum cabin roll rate was saturated. The saturation level was manipulated during the experiment as an independent variable (see below).…”

Section: Setupmentioning

confidence: 99%

Roll rate perceptual thresholds in active and passive curve driving simulation

et al. 2016

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“…The “ compute a circular motion ” block, that bases on the principle of the cylindrical classical MCA, 9 converts the linear lateral trajectory of the frame K P s to the circular one (see dash line in Figure 2(b)). In the block, the given variables are in the blue solid boxes, while the solution (found variables) are in the red dash boxes.…”

Section: Trajectory Generation Of Kuka Robocoastermentioning

confidence: 99%

Auto-Tuning parameters of motion cueing algorithms for high performance driving simulator based on Kuka Robocoaster

Pham

Nguyen

2022

Science Progress

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Driving simulators have been utilized to test and evaluate products and services for a long time. Their complexity and price range from extremely simple low-cost simulators with a fixed base to very complex high-end and pricey six-degree-of-freedom simulators with the XY table. The recent novel technique that uses an industrial robot - KUKA Robocoaster - as an interactive motion simulator platform, allowing for a highly flexible workspace as well as significantly lower prices due to mass production of the fundamental mechanics. In the constrained workspace of driving simulators, motion cueing algorithms (MCAs) are commonly employed to merge the tilt gravity and translational acceleration components for simulating the linear acceleration in the real vehicle. However, there is a few MCAs developed for the motion platform, almost MCAs were implemented for the standard six-degree-of-freedom simulators in the Cartesian coordinate. The classical MCA in the cylindrical coordinate (ClCy) MCA was first developed for the novel motion platform to take advantage of enormous rotational motion to simulate lateral acceleration while compensating for the bothersome longitudinal acceleration (due to centrifugal acceleration appearing in the rotational motion) with a proper pitch tilted angle. The process of tuning MCAs for the novel motion platform is time-consuming due to both trial and error method and the disturbing motion cues generated by rotational motion, thus it needs the involvement of experts. Although there are several auto-tuning approaches for classical, optimal, and model-predictive control MCA based on fuzzy control theory or genetic optimization method, the methods were purely applied for Cartersian coordinate without taking the bothersome longitudinal acceleration into account. Therefore, this paper firstly presents the process of integrating MCAs in the novel motion platform utilizing rotational motion for simulating lateral acceleration. For the case, besides the ClCy algorithm, the classical algorithm developed for the standart six-degree-of-freedom simulators was a sample implementation due to its popular and familiar characteristics. Secondly, the proposal of the use of the mean-variance mapping optimization (MVMO) for auto-tuning parameters of the two algorithms for reducing both rotational false cues in roll and pitch channel, and longitudinal acceleration as well as washout effect. The simulation results prove that 1) The classical and other MCAs can be applied in the novel motion platform with the proposed motion conversion; 2) both algorithms with auto-tuned parameters have high performance in exploiting effectively the workspace of the motion platform, producing no false cues of angular velocity, conpensating the disturbed longitudinal acceleration, and pulling the motion platform to the initial position after the simulation task; 3) The auto-tuning method is so transparent that can manipulates the specific simulated quantities according to the tuning goals.

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“…The effects of the delay, and possible ways to compensate for it in the control design, will be addressed in future studies. Therefore, all the following higher-level control schemes will be built upon the ideal model (1).…”

Section: Description Of the Cybermotion Simulatormentioning

confidence: 99%

“…= f (q i ,q i ) the (acceleration-level) bang-bang law able to stop the i-th joint in minimumtime 1 , with the understanding that the velocity command 1 Since implementation of the classical bang-bang controller has some drawbacks in practical cases, namely overshooting and chattering around the origin because of noise, delays, and discretization, we chose to implement a slightly modified version. Indeed, as proposed in [26], one can avoid these issues by suitably modifying the bang-bang controller behavior in a small neighborhood of the origin, and keeping the same bang-bang characteristics in large.…”

Section: B Differential Inverse Kinematicsmentioning

confidence: 99%

A novel framework for closed-loop robotic motion simulation - part I: Inverse kinematics design

Giordano

Masone

Tesch

et al. 2010

2010 IEEE International Conference on Robotics and Automation

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Abstract-This paper considers the problem of realizing a 6-DOF closed-loop motion simulator by exploiting an anthropomorphic serial manipulator as motion platform. Contrary to standard Stewart platforms, an industrial anthropomorphic manipulator offers a considerably larger motion envelope and higher dexterity that let envisage it as a viable and superior alternative. Our work is divided in two papers. In this Part I, we discuss the main challenges in adopting a serial manipulator as motion platform, and thoroughly analyze one key issue: the design of a suitable inverse kinematics scheme for online motion reproduction. Experimental results are proposed to analyze the effectiveness of our approach. Part II [1] will address the design of a motion cueing algorithm tailored to the robot kinematics, and will provide an experimental evaluation on the chosen scenario: closed-loop simulation of a Formula 1 racing car.

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A novel framework for closed-loop robotic motion simulation - part II: Motion cueing design and experimental validation

Cited by 19 publications

References 16 publications

Roll rate perceptual thresholds in active and passive curve driving simulation

Roll rate perceptual thresholds in active and passive curve driving simulation

Auto-Tuning parameters of motion cueing algorithms for high performance driving simulator based on Kuka Robocoaster

A novel framework for closed-loop robotic motion simulation - part I: Inverse kinematics design

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